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This paper adopts artificial neural network to identify the relationship between personality and handwriting of Chinese characters. The handwriting feature studied here is character spacing, which is extracted by samples scanning and image processing. And the personality factors are obtained by Cattel??s 16PF. Results of 16-8-1 neural network show that the association is significant between 16 personality...
BP algorithm is the typical supervised learning algorithm, so neural network cannot be trained on-line by it. For this reason, a new algorithm(TD-DBP), which was composed of temporal difference (TD) method and dynamic BP algorithm(DBP), was proposed to overcome the restriction. TDDBP algorithm can make Elman network train on-line incrementally. The gradient descent momentum and adaptive learning rate...
Modeling stock returns requires selections of appropriate input variables. For an Artificial Neural Network, the appropriate input variables have both linear and nonlinear functional relationship with stock returns as output variables. To capture the non-linear relationships, we propose Weierstrass theorem. However, to estimate the relationships for all possible combinations of input variables, especially...
In this paper, we describe the neural grammar network (NGN) and its application to quantitative structure-activity relationship (QSAR) in computational chemistry. The NGN is a novel machine learning device that applies the generic function approximation capability of a dynamic recursive neural network to the syntactic structure of a parsed string. In our QSAR task, we represent each molecule by a...
Financial marketing is very common in the world to make money or to control the company strategy. Nearly all events trigger to each other and moreover countries. Some predicting methods, on guessing the marketing depends on natural behavior of the events. When, have a scrutinize to backwards, it can be evaluated that some upfront events occur periodically and trigger to each others and may lead to...
Pointed to the disadvantages such as low recognizing precision, long training time and limited recognizing range of single neural network in eddy current testing, layered multi-subnet neural network is presented. It is composed by a sumnet and several layered subnets, and can divide a complex task into a series of subtasks, so it could quickly identify whether the defect is existed, and also the defect...
This research aims at introducing a system independent method for scour and air entrainment prediction utilizing Artificial Neural Network (ANN) based on previous experimental plunge pool scour tests for inclined circular jets. Furthermore, the current manuscript introduced a single ANN model to predict air entrainment devoid of pre-knowledge of the jet condition either smooth or rough jet. Regarding...
An Echo State Network (ESN) can make multi-step predictions since it can process temporal information without the training difficulties encountered by conventional recurrent neural networks. An ESN is applied in this paper to make multistep predictions of solar irradiance, 30 minutes to 270 minutes into the future. The ESN is trained and tested using two performance metrics (correlation coefficient...
Reducer failure was analyzed and by use of BP neural network in the paper. Model of failure diagnosis was established. By using genetic algorithms, the value of neural networks, the threshold, and the network structure were optimized. Genetic neural network model was applied to the system design of remote reducer fault diagnosis. To compare training error curve of BP neural network with genetic neural...
Eddy current testing (ECT) is becoming a widely used inspection technique, particularly in the aircraft, power and nuclear industries. Many factors may affect the eddy current response. Inverse problems to determine the thickness from ECT signals of multilayer conductors have been a challenge for a certain degree. The objectives of this study are to introduce a method based on improved back propagation...
In this paper a universal steganalysis scheme is proposed for images. The scheme is based on the characteristic function moments of three-level wavelet subbands including the further decomposition coefficients of the first scale diagonal subband. The first three order statistical moments of each band are selected to form a feature vector for steganalysis. The Euclidean distance is used as the separability...
In this paper, a Legendre neural network (LNN) combined with multi-scale stationary wavelet decomposition is used to improve the prediction accuracy and parsimony of monthly anchovy catches forecasting in area north of Chile. The general idea behind this approach is to decompose the observed anchovy catches data into low frequency (LF) component and high frequency (HF) component using the multi-scale...
This paper presents a new approach to image restoration based on ANN, considering the learning of the inverse process using a standard image for training under a multiscale approach. Different models of ANN were tested and compared with the traditional techniques. The standard image was artificially degraded to simulate some types of frequent degradation problems. Due to the huge amount of data generated...
In this paper, an objective way to evaluate artistic voice of singing is discussed. The authors take F1 (the first formant), F3 (the third formant), fundamental frequency, vocal range, perturbation of fundamental frequency, perturbation of F1, perturbation of F3 and average energy as the evaluating parameters and assess the quality of singing voices with BPNN (back propagation neural network). The...
Ankle sprains are one of the most common injuries during sport activities. Gait impairment is a significant problem in ankle sprained cases, leading to decreased activity and limitations in function. The importance of early assessment of sprained ankle is clear. The goal of this early assessment is to start early treatment that can limit the necessary time of rest for the patient. Limiting the rest...
The transmission tower structure damage examination is important safeguard method of power line, this article analyzed the structure damage method based on ARMA model. The warning processing step of tower structure damage was given based on neural network analysis method in this paper, thus the structure damage might be appraised effectively. The 500 KV transmission tower structure damage appraisal...
Wafer defect inspection is an important process that is performed before die packaging. Conventional wafer inspections are usually performed using human visual judgment. A large number of people visually inspect wafers and hand-mark the defective regions. This requires considerable personnel resources and misjudgment may be introduced due to human fatigue. In order to overcome these shortcomings,...
A two-step approach to enhance the resolution of remote sensing thermal infrared (TIR) images is proposed in this paper. For difference in imaging principles between TIR image and optical images, traditional image fusion techniques, such as component substation and MRA methods will not be proper. In our study, we use extreme learning machine (ELM) to regress the relationship between TIR image and...
Two main questions are researched in this paper, which are how to establish the ICC profile, and how to precisely describe and record the device's color rendering characteristic. The process of establishing ICC profile of color printer and data standardization are expounded in detail. An improved BP neural network is used to convert color data between the native device color space and the PCS. Meanwhile,...
This paper has experimentally verified and compared features of sEMG (Surface Electromyogram) such as ICA (Independent Component Analysis) and Fractal Dimension (FD) for identification of low level forearm muscle activities. The fractal dimension was used as a feature as reported in the literature. The normalized feature values were used as training and testing vectors for an artificial neural network...
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